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st: New package -itsa- is available for download from SSC


From   "Ariel Linden" <ariel.linden@gmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: New package -itsa- is available for download from SSC
Date   Mon, 24 Feb 2014 11:51:54 -0500

Thanks to Kit Baum, a new package -itsa- is available for download from SSC
(ssc describe itsa)

-itsa- (interrupted time series analysis) estimates the effect of an
intervention when the outcome variable is ordered as a time series, and a
number of observations are available in both pre- and post-intervention
periods. The study design is generally referred to as an interrupted time
series because the intervention is expected to "interrupt" the level and/or
trend subsequent to its introduction. - itsa- is a wrapper program for, by
default, newey, which produces Newey-West standard errors for coefficients
estimated by OLS regression, or optionally prais, which uses the generalized
least-squares method to estimate the parameters in a linear regression model
in which the errors are assumed to follow a first-order autoregressive
process. itsa estimates treatment effects for either a single treatment
group (with pre- and post-intervention observations) or a multiple-group
comparison (i.e., the single treatment group is compared with one or more
control groups). Additionally, itsa can estimate treatment effects for
multiple treatment periods (which is useful for cross-over studies, or when
the researcher expects that the withdrawal of the intervention will impact
the outcome).

I would like to publically acknowledge the tremendous support that Nick Cox
provided me in writing this program. He is a continued source of inspiration
for me!

I would like to also thank Kit Baum for reviewing the program (after all,
Kit knows time series analysis like no other) and providing valuable
feedback on the use of his program -actest- as a complement to -itsa-... 

We, Statalisters, are indeed fortunate to have access to such incredibly
smart and generous individuals!

Any and all feedback is welcome. 

Ariel




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